In at least one known CT system configuration, an x-ray source projects a fan-shaped beam which is collimated to lie within an X-Y plane of a Cartesian coordinate system and generally referred to as the "imaging plane." The x-ray beam passes through the object being imaged, such as a patient. The beam, after being attenuated by the object, impinges upon an array of radiation detectors. The intensity of the attenuated beam radiation received at the detector array is dependent upon the attenuation of the x-ray beam by the object. Each detector element or cell of the array produces a separate electrical signal that is a measurement of the beam attenuation at that detector location. The attenuation measurements from all the detector cells are acquired separately to produce a transmission profile.
In known CT systems, the x-ray source and the detector array are rotated with a gantry within the imaging plane and around the object to be imaged so that the rotational angle at which the x-ray beam intersects the object constantly changes. A group of x-ray attenuation measurements, i.e., projection data, from the detector array at one gantry rotational angle is referred to as a "view." A "scan" of the object comprises a set of views made at different gantry rotational angles, or view angles, during one revolution of the x-ray source and detector. In an axial scan, the projection data is processed to construct an image that corresponds to a two dimensional slice taken through the object. One method for reconstructing an image from a set of projection data is referred to in the art as the filtered back projection technique. This process converts the attenuation measurements from a scan into integers called "CT numbers" or "Hounsfield units," which are used to control the brightness of a corresponding pixel on a cathode ray tube display and hence produce the image.
As mentioned above, the image corresponds to a two-dimensional slice, or cross-section, of an object. In theory, since the image is two-dimensional, it has no thickness and thereby the measurement flux and detector gain in the z-direction are non-existent and thus uniform. In reality, however, the image is constructed from attenuation measurements supplied by a detector having a finite thickness in the z-direction. The finite thickness of the detector allows for the possibility of a non-uniform measurement flux and a non-uniform detector gain. The inherent thickness of the detector presents problems in trying to construct an accurate two-dimensional image because the composition of the object being scanned (and hence, the measurement flux), as well as the gain of the detector, may vary across the thickness of the detector. In other words, if the attenuation measurement at a certain location comprises part bone and part air, then an image constructed based on the actual attenuation measurement will represent a combination of the bone and air. Similarly, if a bone extends across the entire thickness of the detector, but the detector gain varies across the thickness, then the constructed image will not accurately reflect the composition of the bone. Thus, the attenuation measurements from the detector must be corrected to account for any variation in the detector gain and the measurement flux over the thickness of the image.
These problems are even more pronounced in third generation CT systems using detectors generally known as 2-D detectors. 2-D detectors comprise a plurality of columns and rows of detector cells, where detector cells lined up at different x-locations form a row and detector cells lined up at different z-locations form columns. In a CT system having such a 2-D detector, sometimes referred to as a multislice system, an image may be formed by combining the detector measurements of multiple rows and/or columns of detector cells. Summing a column of cells produces a "macro cell," while macro cells in the same plane produce a "macro row." The detector cell measurements are supplied as inputs to a data acquisition system. If the detector cell measurements to be combined are obtained from detector cells having different individual gains and different fluxes, then the combined measurement represents a weighted sum of the individual detector cell measurements where the different detector cell gains and fluxes cause different weighting. The combined error introduced by detector cell gain and flux differences is object-dependent and cannot be removed by a standard calibration.
To more accurately create an image from such data, it is known to estimate the error due to combining the data from x-ray detector cells having different individual gains. Systems for estimating the error are described in "DETECTOR Z-AXIS GAIN NON-UNIFORMITY CORRECTION IN A COMPUTED TOMOGRAPHY SYSTEM," U.S. Pat. No. 5,734,691, assigned to the present assignee, and "DETECTOR Z-AXIS GAIN CORRECTION FOR A CT SYSTEM," U.S. patent application Ser. No. 08/376,813, filed on Jan. 23, 1995, and assigned to the present assignee. Such correction systems, however, may be improved in a number of respects. Although these systems are able to correct for variations in detector gain measurement flux in the z-direction, the complexity and required computational resources required increase with the order of the correction, i.e. the complexity of the variations in z that must be corrected. This relationship can create conflict between optimizing image quality versus optimizing reconstruction time and cost.
Additionally, these systems comprise a number of z-axis correction factors, where each correction factor depends upon the order of the correction and upon a group of detector segments that the correction is to be applied. Specifically, these systems define a different correction factor for each segment of the detector, where the detector is divided up into a number of segments that overlap in the x-direction. The z-axis correction is then normalized in the x-direction across each segment and the correction for each segment is applied to every detector cell in the segment. The overlapping segments are thereby processed twice, and are smoothed to insure a steady transition from segment to segment. The uniform correction of large segments of the detector, however, tends to skew the correction applied to each individual detector cell or column of cells in the segment. Further, the inclusion of the plurality of overlapping columns requires a duplicative investment in computational time and effort.
Therefore, it would be desirable to more accurately and efficiently create an image from data regardless of the order of the z-axis correction that is required. It further would be desirable to provide such imaging without significantly increasing the cost of the system.